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Computational and Artificial Intelligence Study of the Parameters Affecting the Performance of Heat Recovery Wheels

Received: 30 June 2015     Accepted: 1 July 2015     Published: 14 July 2015
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Abstract

Heat recovery wheels represent key components in air handling units (AHU) that can be used in commercial and industrial building air-conditioning-systems for energy saving. For example, in health facilities, heat transfer process is to be applied in air-conditioning systems for heat recovery of the exhaust (return) air from the patient's room without contamination. Thus, heat recovery wheels are much suitable for such applications. Heat recovery wheels are also known as heat conservation wheels. A conservation wheel consists of a rotor with permeable storage mass fitted in a casing, which operates intermittently between two sections of hot and cold fluids. The rotor is driven by a low-speed electric motor. Thus, the two streams of exhaust and fresh air are alternately passed through the wheel. The present investigation considers computationally the different parameters that affect the operation of heat recovery wheels. These parameters signify actual operating conditions such as flow velocity, shape of cross-section of flow path, and wall material. Moreover, both the artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) techniques were utilized to predict the critical characteristics of the heat exchange system. These artificial intelligence techniques use the present computational results as training and verification data.

Published in American Journal of Energy Engineering (Volume 3, Issue 4-1)

This article belongs to the Special Issue Fire, Energy and Thermal Real-Life Challenges

DOI 10.11648/j.ajee.s.2015030401.16
Page(s) 79-94
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2015. Published by Science Publishing Group

Keywords

Heat Recovery Wheels, Air Handling Units, Computational Study, Artificial Intelligence

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Cite This Article
  • APA Style

    Ahmed F. Abdel Gawad, Muhammad N. Radhwi, Asim M. Wafiah, Ghassan J. Softah. (2015). Computational and Artificial Intelligence Study of the Parameters Affecting the Performance of Heat Recovery Wheels. American Journal of Energy Engineering, 3(4-1), 79-94. https://doi.org/10.11648/j.ajee.s.2015030401.16

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    ACS Style

    Ahmed F. Abdel Gawad; Muhammad N. Radhwi; Asim M. Wafiah; Ghassan J. Softah. Computational and Artificial Intelligence Study of the Parameters Affecting the Performance of Heat Recovery Wheels. Am. J. Energy Eng. 2015, 3(4-1), 79-94. doi: 10.11648/j.ajee.s.2015030401.16

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    AMA Style

    Ahmed F. Abdel Gawad, Muhammad N. Radhwi, Asim M. Wafiah, Ghassan J. Softah. Computational and Artificial Intelligence Study of the Parameters Affecting the Performance of Heat Recovery Wheels. Am J Energy Eng. 2015;3(4-1):79-94. doi: 10.11648/j.ajee.s.2015030401.16

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  • @article{10.11648/j.ajee.s.2015030401.16,
      author = {Ahmed F. Abdel Gawad and Muhammad N. Radhwi and Asim M. Wafiah and Ghassan J. Softah},
      title = {Computational and Artificial Intelligence Study of the Parameters Affecting the Performance of Heat Recovery Wheels},
      journal = {American Journal of Energy Engineering},
      volume = {3},
      number = {4-1},
      pages = {79-94},
      doi = {10.11648/j.ajee.s.2015030401.16},
      url = {https://doi.org/10.11648/j.ajee.s.2015030401.16},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajee.s.2015030401.16},
      abstract = {Heat recovery wheels represent key components in air handling units (AHU) that can be used in commercial and industrial building air-conditioning-systems for energy saving. For example, in health facilities, heat transfer process is to be applied in air-conditioning systems for heat recovery of the exhaust (return) air from the patient's room without contamination. Thus, heat recovery wheels are much suitable for such applications. Heat recovery wheels are also known as heat conservation wheels. A conservation wheel consists of a rotor with permeable storage mass fitted in a casing, which operates intermittently between two sections of hot and cold fluids. The rotor is driven by a low-speed electric motor. Thus, the two streams of exhaust and fresh air are alternately passed through the wheel. The present investigation considers computationally the different parameters that affect the operation of heat recovery wheels. These parameters signify actual operating conditions such as flow velocity, shape of cross-section of flow path, and wall material. Moreover, both the artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) techniques were utilized to predict the critical characteristics of the heat exchange system. These artificial intelligence techniques use the present computational results as training and verification data.},
     year = {2015}
    }
    

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  • TY  - JOUR
    T1  - Computational and Artificial Intelligence Study of the Parameters Affecting the Performance of Heat Recovery Wheels
    AU  - Ahmed F. Abdel Gawad
    AU  - Muhammad N. Radhwi
    AU  - Asim M. Wafiah
    AU  - Ghassan J. Softah
    Y1  - 2015/07/14
    PY  - 2015
    N1  - https://doi.org/10.11648/j.ajee.s.2015030401.16
    DO  - 10.11648/j.ajee.s.2015030401.16
    T2  - American Journal of Energy Engineering
    JF  - American Journal of Energy Engineering
    JO  - American Journal of Energy Engineering
    SP  - 79
    EP  - 94
    PB  - Science Publishing Group
    SN  - 2329-163X
    UR  - https://doi.org/10.11648/j.ajee.s.2015030401.16
    AB  - Heat recovery wheels represent key components in air handling units (AHU) that can be used in commercial and industrial building air-conditioning-systems for energy saving. For example, in health facilities, heat transfer process is to be applied in air-conditioning systems for heat recovery of the exhaust (return) air from the patient's room without contamination. Thus, heat recovery wheels are much suitable for such applications. Heat recovery wheels are also known as heat conservation wheels. A conservation wheel consists of a rotor with permeable storage mass fitted in a casing, which operates intermittently between two sections of hot and cold fluids. The rotor is driven by a low-speed electric motor. Thus, the two streams of exhaust and fresh air are alternately passed through the wheel. The present investigation considers computationally the different parameters that affect the operation of heat recovery wheels. These parameters signify actual operating conditions such as flow velocity, shape of cross-section of flow path, and wall material. Moreover, both the artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) techniques were utilized to predict the critical characteristics of the heat exchange system. These artificial intelligence techniques use the present computational results as training and verification data.
    VL  - 3
    IS  - 4-1
    ER  - 

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Author Information
  • Mech. Eng. Dept., College of Eng. & Islamic Archit., Umm Al-Qura Univ., Makkah, Saudi Arabia

  • Mech. Eng. Dept., College of Eng. & Islamic Archit., Umm Al-Qura Univ., Makkah, Saudi Arabia

  • Mech. Eng. Dept., College of Eng. & Islamic Archit., Umm Al-Qura Univ., Makkah, Saudi Arabia

  • Mech. Eng. Dept., College of Eng. & Islamic Archit., Umm Al-Qura Univ., Makkah, Saudi Arabia

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